Decoding method and device and systems implementing them

ABSTRACT

In order to decode a sequence α=(α 1 , . . . , α i , . . . , α n ) where α i  is the received electrical signal corresponding to a transmitted signal a i  representing the i th  binary element v i  of a word v=(v 1 , . . . , v n ) chosen in a code C of words satisfying v·h T =0, where h is a row n-tuplet on the set {0,1 }, whose number of 1 is denoted w, an item of extrinsic information ρ ext [A(i,h)]=P[a i =−1|A(i,h)]/P[a i =+1|A(i,h)] is determined on each of the elements v i  covered by h, A(i,h) being the set of the received values α j  covered by h, with the exception of α i , and P[a i |A(i,h)] being the probability that the i th  signal transmitted was a i . This gives ρ ext [A(i,h)]=[S 1 (i)+S 3 (i)+ . . . ]/[1+S 2 (i)+S 4 (i)+ . . . ] where the numbers S r (i) are calculated by applying the recurrence 
             r     -   1       ⁢       ∑     i   =   1     w     ⁢       z     α   i       ⁢       S     r   -   1       ⁢     (   i   )             -       z     α   j       ⁢       S     r   -   1       ⁢     (   j   )           =       S   r     ⁢     (   j   )           
 
to the numbers S 0 (i) initialised to 1, with z=exp(−4 E/N), where E is the energy of the transmitted signals a i  and N is the spectral power density of the noise on the transmission channel.

FIELD OF THE INVENTION

The present invention relates to a decoding method and device and to systems using them.

BACKGROUND OF THE INVENTION

The situation is considered where a set of information to be transmitted is represented by a sequence of symbols belonging to the set {0,1}. This set is referred to as the binary alphabet and its elements are referred to as binary elements or bits.

In order to transmit these binary elements, they are converted into electrical quantities. For example, the bit 0 is represented by a positive electrical signal and the bit 1 by a negative electrical signal. These electrical signals have the same absolute value, which is here arbitrarily chosen so as to be equal to 1 in order to simplify the description. However, in reality, these signals can take any value deemed appropriate according to the envisaged application, such as, for example, an electrical voltage of ±5 volts.

When these electrical signals are transmitted over a transmission channel impaired by noise, the received values differ from the transmitted values.

In particular, if the transmission channel is impaired by a white Gaussian noise, the received value a corresponding to a transmitted symbol a belonging to the set {−1,+1} is a random variable whose probability density is given by p(α|a)=(σ√{square root over (2π)})⁻¹exp[−(a−α)²/2σ²], where the parameter σ is specified by the signal to noise ratio of the transmission channel: σ=√{square root over (N/2E)} where N is the spectral power density of the noise and E is the energy of the signal transmitted.

The probability that the symbol a has been transmitted, if α is the symbol received, is denoted P(a|α). The value of ρ(α)=P(−1|α)/P(+1|α) can be used to obtain an estimation â of the transmitted symbol a, received in the form of α: if ρ(α)>1 then â is chosen so as to be equal to −1 and if ρ(α)<1 then â is chosen so as to be equal to +1.

For the purpose of limiting the effect of the noise on the efficacy of the transmission of information, it is known that an error correcting encoding can be implemented, which consists of using only a small proportion of all the possible sequences for representing the information.

An example of such an error correcting encoding is block linear encoding: the binary sequence to be transmitted is a sequence of words of n binary elements, n being a positive integer, each of these words being chosen in the subset C of the words v of length n which satisfy v·H^(T)=0, where H is a matrix of dimension (n−k)×n on the set {0,1}, 0 is the (n−k)-tuplet of zeros and ^(T) represents the transposition, k being an integer less than n. In addition, the components of the matrix product v·H^(T) are calculated modulo 2.

It is well known to a person skilled in the art that any word v of the code C satisfies v·h^(T)=0 for any binary n-tuplet h which is the result of a linear combination of the rows of the matrix H. It should be noted that, in this context, the expression “linear combination” implies that the coefficients which define it are themselves binary elements and the result is always to be reduced modulo 2.

The set of words h thus obtained is referred to as the orthogonal code or dual of the code C and is generally denoted C^(⊥). Let us consider a word h of C^(⊥) whose weight is w (w being an integer less than n), which means that it contains w binary elements equal to 1 and n−w binary elements equal to 0.

Assume, in order to simplify, that these w binary elements equal to 1 appear in the first w positions of h: h=(1, . . . , 1, 0, . . . , 0). Let v=(v₁, . . . , v_(n)). The equation v·h^(T)=0 therefore means ${\sum\limits_{i = 1}^{w}v_{i}} = 0$ modulo 2. It implies in particular: v ₁ =v ₂ +v ₃ + . . . +v _(w) modulo 2  (1) and, more generally, v _(i) =v ₁ + . . . +v _(i−1) +v _(i+1) + . . . +v _(w) modulo 2  (2) for any integer i between 1 and w.

Let a=(a₁, . . . , a_(n)) be the sequence of electrical signals transmitted belonging, in order to simplify, to {−1,+1} and representing the binary n-tuplet v. Let α=(α₁, . . . , α_(n)) be the corresponding received sequence. Equations (1) and (2) above show that, given h, there are, for each of the first w binary values v_(i), two independent items of information which can be extracted from α. The first is the received value α_(i), from which it is possible to calculate ρ(α_(i)) as explained above. The second is the set, denoted A(i,h), of the values α_(j), j=1, . . . , i−1, i+1, . . . , w. This is because, for any i, the values α_(j) of A(i,h) are a noisy image of the corresponding symbols a_(j), which are a faithful translation of the corresponding binary elements v_(j).

In order to explain this second item of information, said to be extrinsic, on v_(i), the quantity z=exp(−2/σ²)=exp(−4E/N) is introduced, which depends on the signal to noise ratio of the transmission channel in question, and there are defined: S ₁(i)=Σz ^(α) ^(j) ,α_(j) εA(i,h), S ₂(i)=Σz ^(α) ^(j) ^(+α) ^(k) ,α_(j), α_(k) εA(i,h),j<k, S ₃(i)=Σz ^(α) ^(j) ^(+α) ^(k) ^(+α) ^(l) ,α_(j),α_(k),α_(l) εA(i,h),j<k<l, . . . S _(w−1)(i)=z ^(α) ¹ ^(+ . . . +α) ^(i−1) ^(+α) ^(i+1) ^(+ . . . +α) ^(w)

P[a_(i)|A(i,h)] is defined as being the probability that the i^(th) signal transmitted was a_(i) given the symbols α_(j) of A(i,h). The quantity ρ_(ext)[A(i,h)]=P[a_(i)=−1|A(i,h)]/P[a_(i)=+1|A(i,h)] supplies “additional information” on the value of the transmitted symbol a_(i).

It can be shown that the quantities ρ_(ext)[A(i,h)] have a very simple expression according to the polynomials S_(r)(i) introduced above: ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . . ]

When methods of the probabilistic type are used for estimating what was the transmitted sequence (or only some of its binary elements), the following problem is posed: it is sought to determine the quantities ρ_(ext)[A(i,h)] for i=1, . . . , w with a calculation cost as low as possible, on the basis of the w binary elements received represented by the received signals α_(j), corresponding to a word h of the code C^(⊥).

SUMMARY OF THE INVENTION

The purpose of the present invention is to afford a solution to the aforementioned problem.

To this end, the present invention proposes a method of decoding a received sequence α=(α₁, . . . , α_(n)) where, for any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i) representing the i^(th) binary element v_(i) of a word chosen in a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and the scalar product v·h^(T) is calculated modulo 2,

-   -   this decoding method including a step consisting of determining         extrinsic information on each of the binary elements of v         covered by h, the extrinsic information given on the i^(th)         binary element of v, assumed to be covered by h, being the         quantity ρ_(ext)[A(i,h)]=P[a_(i)=−1|A(i,h)]/P[a_(i)=+1|A(i,h)],         where A(i,h) is the set of received values α_(j) of α which are         covered by h, with the exception of α_(i), and where         P[a_(i)|A(i,h)] is the probability, calculated on the basis of         the received signals α_(j) of A(i,h), that the i^(th) signal         transmitted was a_(i),     -   this decoding method being remarkable in that the determination         of the extrinsic information is effected by means of the formula         ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . .         ]         where the numbers S_(r)(i), for any integer r between 1 and w−1,         are calculated by applying the recurrence         ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$         to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where         E is the energy of the transmitted signal a_(i) and N is the         spectral power density of the noise on the transmission channel.

It is said that the word h covers the index position i (of v, a or α) if the binary element of h in position i is 1.

The present invention thus makes it possible to simplify the calculation of the quantities ρ_(ext)[A(i,h)], which can thus be effected in a number of steps which can be expressed in polynomial form according to the weight w of h.

According to a particular characteristic, a supplementary item of extrinsic information is determined on each of the binary elements of v covered by h by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{{\underset{\_}{\rho}\left( \alpha_{i} \right)}{S_{r - 1}(i)}}}} - {{\underset{\_}{\rho}\left( \alpha_{j} \right)}{S_{r - 1}(j)}}} = {S_{r}(j)}$ where ρ(α_(i)) represents the ratio between the probability that a_(i) is equal to −1 and the probability that a_(i) is equal to +1, these probabilities taking into account at least part of the extrinsic information calculations already made.

Thus the extrinsic information already calculated can be used iteratively.

According to a particular characteristic, the quantity ρ(α_(i)) is given by ρ(α_(i))=ρ(α_(i))·ρ_(ext)[A(i,h)] where ρ(α_(i))=P(−1|α_(i))/P(+1|α_(i)), P(a_(i)|α_(i)) designating the probability that the i^(th) signal transmitted was a_(i) if the i^(th) signal received is α_(i).

According to a particular characteristic, the decoding method of the invention is implemented in a turbodecoding method.

This simplifies this turbodecoding method without weakening its effectiveness.

According to a particular characteristic, the calculations relating to the aforementioned recurrence are effected in multiple precision.

Thus the precision of the calculations is not affected by the calculation of the differences, which is inherent in the proposed decoding method.

For the same purpose as indicated above, the present invention also proposes a device for decoding a received sequence α=(α₁, . . . , α_(n)) where, for any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i) representing the i^(th) binary element v_(i) of a word chosen in a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and the scalar product v·h^(T) is calculated modulo 2,

-   -   this decoding device having means for determining extrinsic         information on each of the binary elements of v covered by h,         the extrinsic information given on the i^(th) binary element of         v, assumed to be covered by h, being the quantity         ρ_(ext)[A(i,h)]=P[a_(i)=−1|A(i,h)]/P[a_(i)=+1|A(i,h)], where         A(i,h) is the set of received values α_(j) of α which are         covered by h, with the exception of α_(i), and where         P[a_(i)|A(i,h)] is the probability, calculated on the basis of         the received signals α_(j) of A(i,h), that the i^(th) signal         transmitted was a_(i),     -   this decoding device being remarkable in that the determination         of the extrinsic information is effected by means of the formula         ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . .         ]         where the numbers S_(r)(i), for any integer r between 1 and w−1,         are calculated by applying the recurrence         ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$         to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where         E is the energy of the transmitted signals a_(i) and N is the         spectral power density of the noise on the transmission channel.

Thus the calculation of the quantities ρ_(ext)[A(i,h)] requires a device whose complexity is only polynomial in the weight w of h.

In addition, the particular characteristics of the decoding device, which are not explained below, and their advantages, are similar to those of the decoding method and will therefore not be stated here.

In a particular embodiment, the device has:

-   -   a plurality of multipliers, each of the multipliers receiving,         at a first input, the value of S_(r−1)(i) and, at its second         input, the value −z^(α) ^(i) ;     -   a plurality of adders, a first input of each of the adders being         respectively connected to the output of each of the multipliers;     -   an adding module, whose input is connected to the output of each         of the multipliers;     -   an additional multiplication module, a first input of which is         connected to the output of the adding module and the second         input of which receives the value −1/r, the output of the         additional multiplication module being connected to the second         input of each of the adders; and     -   a delay introduction module, whose input is connected to the         output of each of the adders and whose output is connected to         the first input of each of the multipliers,         this device being initialised by S₀(i)=1 for any i, so that each         of the adders outputs the value S_(r)(i).

In a particular embodiment, several of the calculations necessary for determining the extrinsic information can be made by circuits put in parallel.

In another embodiment, several of the calculations necessary for determining the extrinsic information can be made by circuits put in series.

The present invention also relates to a digital signal processing apparatus, having means adapted to implement a decoding method as above.

The present invention also relates to a digital signal processing apparatus, having a decoding device as above.

The present invention also relates to a telecommunications network, having means adapted to implement a decoding method as above.

The present invention also relates to a telecommunications network, having a decoding device as above.

The present invention also relates to a mobile station in a telecommunications network, having means adapted to implement a decoding method as above.

The present invention also relates to a mobile station in a telecommunications network, having a decoding device as above.

The present invention also relates to a device for processing signals representing speech, including a decoding device as above.

The present invention also relates to a data transmission device having a transmitter adapted to implement a packet transmission protocol, having a decoding device and/or a device for processing signals representing speech as above.

According to a particular characteristic of the data transmission device, the packet transmission protocol is of the ATM (Asynchronous Transfer Mode) type.

As a variant, the packet transmission protocol is of the IP (Internet Protocol) type.

The invention also relates to:

-   -   an information storage means which can be read by a computer or         microprocessor storing instructions of a computer program,         making it possible to implement a decoding method as above, and     -   an information storage means which is removable, partially or         totally, and which can be read by a computer or microprocessor         storing instructions of a computer program, making it possible         to implement a decoding method as above. By way of non-limiting         example, such a removable storage means may be a floppy disk or         a CD-ROM or a DVD-ROM.

The invention also relates to a computer program containing sequences of instructions for implementing a decoding method as above.

The particular characteristics and the advantages of the different digital signal processing apparatus, the different telecommunications networks, the different mobile stations, the device for processing signals representing speech, the data transmission device, the information storage means and the computer program being similar to those of the decoding method according to the invention, they are not stated here.

Other aspects and advantages of the invention will emerge from a reading of the following detailed description of particular embodiments, given by way of non-limitative examples. The description refers to the drawings which accompany it, in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts schematically a circuit for the simultaneous calculation of the quantities S_(r)(j) using a decoding method according to the present invention, in a particular embodiment;

FIG. 2 depicts schematically a mode of iterative use of the circuit of FIG. 1;

FIG. 3 depicts schematically a more general embodiment of the circuit for calculating the quantities S_(r)(j), in which this calculation is made using information ρ(α_(i)i) more general than the simple knowledge of the received symbols α_(i);

FIG. 4 illustrates schematically the application of the invention to the field of turbocodes, in a particular embodiment;

FIG. 5 is a flow diagram illustrating steps of a decoding method according to the present invention; and

FIG. 6 depicts schematically an electronic device including a decoding device according to the present invention, in a particular embodiment.

DETAIL DESCRIPTION OF THE PREFERRED EMBODIMENTS

A received sequence α=(α₁, . . . , α_(n)), which was passed through a transmission channel impaired by white Gaussian noise, is considered below.

For any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i). The electrical signal a_(i) represents the i^(th) binary element v_(i) of a word v chosen in a code C of words satisfying v·h^(T)=0, where h is a row n-tuplet of binary elements whose number of 1 is denoted w, where ^(T) represents the transposition and where the scalar product v·h^(T) is calculated modulo 2.

The decoding method of the invention includes a step consisting of determining extrinsic information on each of the binary elements v_(i) of said to be covered by h=(h₁, . . . , h_(n)), that is to say for any i such that h_(i)=1. It is said in fact that the word h covers the position of index i of v if the binary element of h in position i is 1.

The method proposed will be illustrated by the example, in no way limitative, where w=4.

From the definitions given in the introduction, the following expressions arise:

 S ₁(1)=z ^(α) ² +z ^(α) ³ +z ^(α) ⁴ , S ₁(2)=z ^(α) ¹ +z ^(α) ³ +z ^(α) ⁴ , S ₁(3)=z ^(α) ¹ +z ^(α) ² +z ^(α) ⁴ , S ₁(4)=z ^(α) ¹ +z ^(α) ² +z ^(α) ³ , S ₂(1)=z ^(α) ² ^(+α) ³ +z ^(α) ² ^(+α) ⁴ +z ^(α) ³ ^(+α) ⁴ , S ₂(2)=z ^(α) ¹ ^(+α) ³ +z ^(α) ¹ ^(+α) ⁴ +z ^(α) ³ ^(+α) ⁴ , S ₂(3)=z ^(α) ¹ ^(+α) ² +z ^(α) ¹ ^(+α) ⁴ +z ^(α) ² ^(+α) ⁴ , S ₂(4)=z ^(α) ¹ ^(+α) ² +z ^(α) ¹ ^(+α) ³ +z ^(α) ² ^(+α) ³ , S ₃(1)=z ^(α) ² ^(+α) ³ ^(+α) ⁴ , S ₃(2)=z ^(α) ¹ ^(+α) ³ ^(+α) ⁴ , S ₃(3)=z ^(α) ¹ ^(+α) ² ^(+α) ⁴ , S ₃(4)=z ^(α) ¹ ^(+α) ² ^(+α) ³ .

It can be checked that the above expressions satisfy the following equations: ${{{\sum\limits_{i = 1}^{4}{z^{\alpha_{i}}{S_{1}(i)}}} - {2z^{\alpha_{j}}{S_{1}(j)}}} = {2{S_{2}(j)}}},{{{\sum\limits_{i = 1}^{4}{z^{\alpha_{i}}{S_{2}(i)}}} - {3z^{\alpha_{j}}{S_{2}(j)}}} = {3{{S_{3}(j)}.}}}$

These equations are particular cases of more general equations valid for any w. In fact let S₀(i)=1 for any i. For r=1, . . . , w−1: $\begin{matrix} {{{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}} = {r{\sum z^{\alpha_{j_{1}} + \ldots\quad + \alpha_{j_{r}}}}}},} & (3) \\ {{{{rz}^{\alpha_{j}}{S_{r - 1}(j)}} = {r{\sum z^{\alpha_{j_{1}} + \ldots + \alpha_{j_{r - 1}} + \alpha_{j}}}}},} & (4) \end{matrix}$ where, in the right-hand member of equation (3), the sum relates to all the r-tuplets (j₁, . . . , j_(r)) of integers between 1 and w (including delimiters) and satisfying j₁<j₂< . . . <j_(r), and where, in the right-hand member of equation (4), the sum relates to all the (r−1)-tuplets (j₁, . . . , j_(r−1)) of integers which are different and not equal to j, between 1 and w (including delimiters) and satisfying j₁<j₂< . . . <j_(r−1).

It is verified that the difference between the right-hand members of equations (3) and (4) is given by: rΣz ^(α) ^(j) ₁ ^(+ . . . +α) ^(j) _(r) −rΣz ^(α) ^(j) ₁ ^(+ . . . +α) ^(j) _(r−1) ^(+α) ^(j) =rS _(r)(j), from which: ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {{S_{r}(j)}.}$

The interpretation of the terms of this recurrence is as follows. The sum $r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}$ includes once and only once each monomial obtained as the product of r different factors z^(α) ^(i) . The term z^(α) ^(j) S_(r−1)(j) includes once and only once each monomial obtained as the product of r different factors z^(α) ^(i) , under the constraint that the monomial z^(α) ^(j) is a factor of each of these monomials. Consequently the difference between these two expressions is indeed the sum of all the monomials obtained as a product of r different factors z^(α) ^(i) amongst which the monomial z^(α) ^(j) does not appear, that is to say S_(r)(j).

This recurrence makes it possible, for r>0, to determine all the S_(r)(j) values for j=1, . . . , w as soon as all the S_(r−1)(j) values are known for j=1, . . . , w.

Given that the use of this recurrence entails the calculation of a difference, it is advantageous to make the calculations in multiple precision, in order to avoid the conventional problem of lack of precision in the result, which can be posed when this result is small compared with the terms whose difference is being calculated.

To this end, it is for example possible to represent the quantities manipulated by a number of binary elements twice as great as the minimum necessary.

The present invention lends itself particularly well to implantations of the “serial” or “parallel” type, using a very simple base circuit, illustrated in FIG. 1. This circuit is in fact adapted to the iterative calculation of the w·(w−1) values S_(r)(i) for i=1, . . . , w and r=1, . . . , w−1.

It has a series of multipliers 10 ₁, 10 ₂, 10 ₃, . . . , 10 _(w), each multiplier 10 _(i) receiving, at a first input, the value of S_(r−1)(i) and, at its second input, the value −z^(α) ^(i) .

The circuit also includes a series of adders 12 ₁, 12 ₂, 12 ₃, . . . , 12 _(w). The output of each multiplier 10 _(i) is connected to a first input of the adder 12 _(i).

The output of each multiplier 10 _(i) is also connected to the input of a single adding module 14. The output of the adding module 14 is connected to a first input of a multiplier 16, which receives at its second input the value −1/r.

The output of the multiplier 16 is connected to the second input of each adder 12 _(i).

Thus each adder 12 _(i) outputs the value S_(r)(i).

It suffices to initialise the inputs of the circuit by S₀(i)=1 for any i. For r=1, the circuit calculates in one step all the values S₁(i), i=1, . . . , w. Using these values S₁(i) at the input of the circuit with r=2, the values S₂(i) are obtained; by continuing in this way, the values S_(r)(i) for any r are obtained. FIG. 2 illustrates schematically this iterative functioning mode.

FIG. 2 is identical to FIG. 1 and will therefore not be described again here, except that the outputs of the adders 12 ₁, 12 ₂, 12 ₃, . . . , 12 _(w) are respectively connected to the inputs of the multipliers 10 ₁, 10 ₂, 10 ₃, . . . , 10 _(w) by means of a matrix of delay elements 18, which makes it possible to use the recurrence giving the values S_(r)(i) according to the values S_(r−1)(i).

It is also possible to form a global circuit by disposing in cascade w−1 circuits like the one in FIG. 2 and initialising the first of them by S₀(i)=1 for any i. In this case, the w values S_(r)(i), i=1, . . . , w appear as outputs of the r^(th) stage of the global circuit.

It is also possible to dispose a predetermined number of circuits like the one in FIG. 1 in parallel, in an iterative version (like the one in FIG. 2) or in cascade, in order to simultaneously calculate several different items of extrinsic information corresponding to parity relationships specified by different words h of the dual code C^(⊥.)

The invention has a particular application for turbodecoding.

In the above, the case of a transmission channel with white Gaussian noise was considered, along with the determination of extrinsic information obtained via one or more words h of the code C^(⊥) orthogonal to the code C used for transmission.

However, after having determined, on the basis of one or more words h of C^(⊥), one or more items of extrinsic information concerning the values of the transmitted symbols, it may be effective, as shown by recent works with regard to turbocodes (see for example the article by R. Pyndiah entitled “Near optimum decoding of product codes: block turbo codes”, in IEEE Transactions on Communications, 46, No. 8, pages 1003 to 1010, August 1998), to calculate new items of extrinsic information, on the basis not only of the values ρ(a)=P(−1|α)/P(+1|α), but on the basis of values ρ(α) taking into account all or part of the extrinsic information calculations already made. This remark is at the basis of the iterative decoding of error correcting codes. As indicated in the article by R. Pyndiah, the product codes lend themselves particularly well to this type of decoding. In particular, if, on the basis of one or more words h of C^(⊥), quantities ρ_(ext)[A(i,h)] have been calculated, it is possible to calculate new extrinsic information items, on the basis no longer only of the values ρ(α_(i))=P(−1|α_(i))/P(+1|α_(i)), but on the basis of the products ρ(α_(i))·ρ_(ext)[A(i,h)].

The circuit described above with the help of FIG. 1 can easily be used for this purpose. This is because, in this circuit, the ρ(α_(i)) values are represented by the parameters z^(α) ^(i) : this gives ρ(α_(i))=z^(αi) . Thus, if, at any time in the decoding, there is extrinsic information represented globally by new values ρ(α_(i)) of the values ρ(α_(i)), it suffices to replace in FIG. 1 the multiplicative coefficients z^(α) ^(i) by these new coefficients ρ(α_(i)). The recurrence used is then ${{r^{- 1}{\sum\limits_{i = 1}^{w}{{\underset{\_}{\rho}\left( \alpha_{i} \right)}{S_{r - 1}(i)}}}} - {{\underset{\_}{\rho}\left( \alpha_{j} \right)}{S_{r - 1}(j)}}} = {S_{r}(j)}$ where ρ(α_(i)) represents the ratio between the probability that a_(i) is equal to −1 and the probability that a_(i) is equal to +1.

Whatever the way in which the changes in the n values ρ(α_(i)) corresponding to the n binary elements v_(i) transmitted, or, equivalently, to the n electrical signals as which represent them, are managed, the estimation of a_(i) will be −1 if the final value of ρ(α_(i)) is strictly positive and will be +1 if the final value of ρ(α_(i)) is strictly negative.

FIG. 3 depicts schematically this type of use of the circuit of FIG. 1, in the case of an implantation of the iterative type. It will not be described in any further detail given that the elements making up the circuit are the same and bear the same reference numbers as the elements already described with the help of FIGS. 1 and 2.

A use of the invention for decoding data using turbocodes is depicted schematically in FIG. 4. In order to simplify, the notations set out in the figure concern only one iteration of the decoding.

From the received sequence (α_(i), . . . , α_(n)), from extrinsic information already calculated ρ(α_(i)) and from a word h of C^(⊥), new extrinsic information ρ_(ext)[A(i,h)] is calculated for all the positions i covered by h. This is illustrated by an extrinsic information determination block 40 in FIG. 4. Next this extrinsic information ρ_(ext)[A(i,h)] is recombined with that already calculated ρ(α_(i)) in order to update this extrinsic information already calculated ρ(α_(i)). This is illustrated by a recombination and updating block 42.

Concerning the choice of the word h, by way of in no way limitative example, it will for example be possible to use one and the same word h in several non-consecutive iterations. Nevertheless, neither the optimisation of the choice of h, nor the mode of recombining the extrinsic information ρ_(ext)[A(i,h)] with the information ρ(α_(i)), when the latter is updated, are within the scope of the present invention. These elements are therefore not described in detail here.

The flow diagram in FIG. 5 illustrates steps of a decoding method according to the present invention.

As shown in FIG. 5, it is assumed that electrical signals a representing respectively binary elements v_(i) of a word v have previously been transmitted. As described above, the word v is chosen from a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and where the scalar product v·h^(T) is calculated modulo 2.

It is also assumed that a sequence α=(α₁, . . . , α_(n)) of electrical signals has been received, where the received signal α_(i), 1≦i≦n corresponds respectively to the transmitted signal a_(i), 1≦i≦n.

A step 500 of initialising the decoding method according to the invention then consists of initialising a variable denoted r to the value 0 and initialising the quantities S_(r)(i) defined above to the value 1 for any i between 1 and w, that is to say S₀(i)=1∀i, 1≦i≦w.

Then the recurrence on r is effected as follows:

-   -   an incrementation step 502 consists of increasing the value of r         by one unit,     -   an extrinsic information determination step 504 consists of         obtaining S_(r)(i) from the knowledge of S_(r−1)(i), and this         for all the values of i between 1 and w, as described above, and     -   a test 506 consists of determining whether or not the value of r         has reached the value w−1.

If test 506 is negative, steps 502, 504 and 506 are reiterated.

If test 506 is positive, this means that r=w−1; S_(w−1)(i) has then been obtained for i between 1 and w.

As already described, for all the positions i covered by h and for all the values of i between 1 and w, there is then derived therefrom extrinsic information on v_(i) denoted ρ_(ext)[A(i,h)] and defined as being equal to P[a_(i)=−1|A(i,h)]/P[a_(i)=+1|A(i,h)], where A(i,h) is the set of the received values α_(j) of α which are covered by h, with the exception of α_(i), and where P[a_(i)|A(i,h)] is the probability, calculated on the basis of the received signals α_(j) of A(i,h), that the i^(th) signal transmitted was a_(i).

As described above, the extrinsic information is determined by means of the formula ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . . ] where the numbers S_(r)(i), for any integer r between 1 and w−1, are calculated by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$ to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where E is the energy of the transmitted signals a_(i) and N is the spectral power density of the noise on the transmission channel.

FIG. 6 illustrates schematically the constitution of a network station or computer decoding station, in the form of a block diagram.

This station has a keyboard 311, a screen 309, an external information destination 310, and a radio receiver 306, conjointly connected to an input/output port 303 of a processing card 301.

The processing card 301 has, connected together by an address and data bus 302:

-   -   a central processing unit 300;     -   a random access memory RAM 304;     -   a read only memory ROM 305; and     -   the input/output port 303.

Each of the elements illustrated in FIG. 6 is well known to a person skilled in the art of microcomputers and transmission systems and, more generally, information processing systems. These common elements are therefore not described here. It should however be noted that:

-   -   the information destination 310 is, for example, an interface         peripheral, a display, a modulator, an external memory or other         information processing system (not shown), and is advantageously         adapted to receive sequences of signals representing speech,         service messages or multimedia data, in the form of binary data         sequences, and that     -   the radio receiver 306 is adapted to implement a packet         transmission protocol on a non-cabled channel, and to receive         packets over such a channel.

It should also be noted that the word “register” used in the description designates, in each of the memories 304 and 305, both a memory area of low capacity (a few binary data) and a memory area of large capacity (making it possible to store an entire program).

The random access memory 304 stores data, variables and intermediate processing results, in memory registers bearing, in the description, the same names as the data whose values they store. The random access memory 304 contains notably:

-   -   a register “received_data”, in which there are stored the binary         data received, in their order of arrival on the bus 302 coming         from the transmission channel,     -   a register “extrinsic_inf”, in which there are stored, at a         given moment, the extrinsic information corresponding to each         binary element v_(i) of a word v, and     -   a register “S_(r)(i)”, in which there are stored the values of         the numbers S_(r)(i) as they are calculated.

The read only memory 305 is adapted to store the operating program of the central processing unit 300, in a register “Program”.

The central processing unit 300 is adapted to implement the embodiments illustrated by FIGS. 1 to 3 and/or the application to the turbocodes illustrated by FIG. 4 and/or the flow diagram of FIG. 5.

As a variant, the invention could be implemented not only by software method but possibly by using hard-wired or programmable logic. 

1. A method of decoding a received sequence α=(α₁, . . . , α_(n)) where, for any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i) representing the i^(th) binary element v_(i) of a word chosen in a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and the scalar product v·h^(T) is calculated modulo 2, said decoding method including a step consisting of determining extrinsic information on each of the binary elements of v covered by h, said extrinsic information given on the i^(th) binary element of v, assumed to be covered by h, being the quantity ρ_(ext) [A(i,h)]=P[a _(i)=−1|A(i,h)]/P[a _(i)=+1|A(i,h)], where A(i,h) is the set of received values α_(j) of α which are covered by h, with the exception of α_(i), and where P[a_(i)|A(i,h)] is the probability, calculated on the basis of the received signals α_(j) of A(i,h), that the i^(th) signal transmitted was a_(i), said decoding method being characterised in that the determination of the extrinsic information is effected by means of the formula ρ _(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . . ] where the numbers S_(r)(i), for any integer r between 1 and w−1, are calculated by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$ to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where E is the energy of the transmitted signals a_(i) and N is the spectral power density of the noise on the transmission channel.
 2. A method according to claim 1, wherein a supplementary item of extrinsic information is determined on each of the binary elements of v covered by h by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{{\underset{\_}{\rho}\left( \alpha_{i} \right)}{S_{r - 1}(i)}}}} - {{\underset{\_}{\rho}\left( \alpha_{j} \right)}{S_{r - 1}(j)}}} = {S_{r}(j)}$ where ρ(α_(i)) represents the ratio between the probability that a_(i) is equal to −1 and the probability that a_(i) is equal to +1, these probabilities taking into account at least part of the extrinsic information calculations already made.
 3. A method according to claim 2, wherein the quantity ρ(α_(i)) is given by ρ(α_(i))=ρ(α_(i))·ρ_(ext)[A(i,h)] where ρ(α_(i))=P(−1|α_(i))/P(+1|α_(i)), P(a_(i)|α_(i)) designated the probability that the i^(th) signal transmitted was a_(i) if the i^(th) signal received is α_(i).
 4. A method according to claim 1, 2 or 3, wherein it is implemented in a turbodecoding method.
 5. A method according to 1, 2 or 3, wherein the calculations relating to said recurrence are made in multiple precision.
 6. Digital signal processing apparatus, having means adapted to implement a decoding method according to claim 1, 2 or
 3. 7. A telecommunications network, having means adapted to implement a decoding method according to claim 1, 2 or
 3. 8. A mobile station in a telecommunications network, having means adapted to implement a decoding method according to claim 1, 2 or
 3. 9. A device for decoding a received sequence α=(α₁, . . . , α_(n)) where, for any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i) representing the i^(th) binary element v_(i) of a word chosen in a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and the scalar product v·h^(T) is calculated modulo 2, said decoding device having means for determining extrinsic information on each of the binary elements of v covered by h, said extrinsic information given on the i^(th) binary element of v, assumed to be covered by h, being the quantity ρ_(ext) [A(i,h)]P[a _(i)=−1|A(i,h)]/P[a _(i)=+1|A(i,h)], where A(i,h) is the set of received values α_(j) of α which are covered by h, with the exception of α_(i), and where P[a_(i)|A(i,h)] is the probability, calculated on the basis of the received signals α_(j) of A(i,h), that the i^(th) signal transmitted was a_(i), said decoding device being characterised in that the determination of the extrinsic information is effected by means of the formula ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+ . . . ]/[1+S ₂(i)+S ₄(i)+ . . . ] where the numbers S_(r)(i), for any integer r between 1 and w−1, are calculated by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$ to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where E is the energy of the transmitted signals a_(i) and N is the spectral power density of the noise on the transmission channel.
 10. A device according to claim 9, further comprising means for determining an additional item of extrinsic information on each of the binary elements of v covered by h by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{w}{{\underset{\_}{\rho}\left( \alpha_{i} \right)}{S_{r - 1}(i)}}}} - {{\underset{\_}{\rho}\left( \alpha_{j} \right)}{S_{r - 1}(j)}}} = {S_{r}(j)}$ where ρ(α_(i)) represents the ratio between the probability that a_(i) is equal to −1 and the probability that a_(i) is equal to +1, these probabilities taking into account at least part of the extrinsic information calculations already made.
 11. A device according to claim 10, wherein the quantity ρ(α_(i)) is given by ρ(α_(i))=ρ(α_(i))·ρ_(ext)[A(i,h)] where ρ(α_(i))=P(−1|α_(i))/P(+1|α_(i)), P(a_(i)|α_(i)) designating the probability that the i^(th) signal transmitted was a_(i) if the i^(th) signal received is α_(i).
 12. A device according to claim 9, 10 or 11, having: a plurality of multipliers, each of said multipliers receiving, at a first input, the value of S_(r−1)(i) and, on its second input, the value −Z^(α) ^(i) ; a plurality of adders, a first input of each of said adders being respectively connected to the output of each of said multipliers; adding means, whose input is connected to the output of each of said multipliers; additional multiplication means, a first input of which is connected to the output of said adding means and the second input of which receives the value −1/r, the output of said additional multiplication means being connected to the second input of each of said adders; and delay introduction means, whose input is connected to the output of each of said adders and whose output is connected to the first input of each of said multipliers, said device being initialised by S₀(i)=1 for any i, so that each of said adders outputs the value S_(r)(i).
 13. A device according to claim 9, 10 or 11, said device being used in a turbodecoder.
 14. A device according to claim 9, 10 or 11, wherein the calculations relating to said recurrence are effected in multiple precision.
 15. A device according to claim 9, 10 or 11, wherein the implementation of several of the calculations necessary for determining the extrinsic information is made by circuits put in parallel.
 16. A device according to claim 9, 10 or 11, wherein the implementation of several of the calculations necessary for determining the extrinsic information is made by circuits put in series.
 17. Digital signal processing apparatus, having a decoding device according to claim 9, 10, or
 11. 18. A telecommunications network, having a decoding device according to claim 9, 10 or
 11. 19. A mobile station in a telecommunications network, having a decoding device according to claim 9, 10 or
 11. 20. A device for processing signals representing speech, including a decoding device according to claim 9, 10 or
 11. 21. An information storage means which can be read by a computer or microprocessor, the storage means storing instructions of a computer program that, when implemented, causes the computer to execute a method of decoding a received sequence α=(α₁, . . . , α_(n)) where, for any integer i between 1 and n, n being an integer greater than 1, α_(i) is the received electrical signal corresponding to the transmission of an electrical signal a_(i) representing the i^(th) binary element v_(i) of a word chosen in a binary code C of words v=(v₁, . . . , v_(n)) satisfying v·h^(T)=0, where h is a row n-tuplet on the set {0,1} whose number of 1 is denoted w, where ^(T) represents the transposition and the scalar product v·h^(T) is calculated modulo 2, said decoding method including a step consisting of determining extrinsic information on each of the binary elements of v covered by h, said extrinsic information given on the i^(th) binary element of v, assumed to be covered by h, being the quantity ρ_(ext) [A(i,h)]=P[a _(i)=−1|A(i,h)]/P[a _(i)=+1A(i,h)], where A(i,h) is the set of received values α_(j) of α which are covered by h, with the exception of α_(i), and where P[a_(i)|A(i,h)] is the probability, calculated on the basis of the received signals α_(j) of A(i,h), that the i^(th) signal transmitted was a_(i), said decoding method being characterized in that the determination of the extrinsic information is effected by means of the formula ρ_(ext) [A(i,h)]=[S ₁(i)+S ₃(i)+. . . ]/[1+S ₂(i)+S ₄(i)+. . . ] where the numbers S_(r)(i), for any integer r between 1 and w−1, are calculated by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{W}{z^{\alpha_{i}}{S_{r - 1}(i)}}}} - {z^{\alpha_{j}}{S_{r - 1}(j)}}} = {S_{r}(j)}$ to the numbers S₀(i) initialised to 1, with z=exp(−4E/N), where E is the energy of the transmitted signals a_(i) and N is the spectral power density of the noise on the transmission channel.
 22. An information storage means according to claim 21, wherein the storage means is partially or totally removable.
 23. An information storage means according to claim 22, wherein a supplementary item of extrinsic information is determined on each of the binary elements of v covered by h by applying the recurrence ${{r^{- 1}{\sum\limits_{i = 1}^{W}{{\underset{\_}{\rho}\left( \alpha_{i} \right)}{S_{r - 1}(i)}}}} - {{\underset{\_}{\rho}\left( \alpha_{j} \right)}{S_{r - 1}(j)}}} = {S_{r}(j)}$ where ρ(α_(i)) represents the ratio between the probability that a_(i) is equal to −1 and the probability that a_(i) is equal to +1, these probabilities taking into account at least part of the extrinsic information calculations already made.
 24. An information storage means according to claim 22, wherein the quantity ρ(α_(i)) is given by ρ(α_(i))=ρ(α_(i))·ρ_(ext)[A(i,h)] where ρ(α_(i))=P(−1|α_(i))/P(+1|α_(i)), P(a_(i)|α_(i)) designated the probability that the i^(th) signal transmitted was a_(i) if the i^(th) signal received is α_(i). 